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    题名: Exploring the relationships between annual earnings and subjective expressions in US financial statements
    作者: Chen, Chien-Liang;Liu, Chao-Lin;Chang, Yuan-Chen;Tsai, H.-P.
    陳建良;劉昭麟;張元晨
    贡献者: 經濟學系;資訊科學系;財管系
    关键词: Information Extraction;NAtural language processing;Opinion mining;Sentiment analysis;Text mining;Algorithms;Artificial intelligence;Computational linguistics;Electronic commerce;Industry;Natural language processing systems;Profitability;Random processes;Finance
    日期: 2011-10
    上传时间: 2015-10-08 17:51:12 (UTC+8)
    摘要: Subjective assertions in financial statements influence the judgments of market participants when they assess the value and profitability of the reporting corporations. Hence, the managements of corporations may attempt to conceal the negative and to accentuate the positive with "prudent" wording. To excavate this accounting phenomenon hidden behind financial statements, we designed an artificial intelligence based strategy to investigate the linkage between financial status measured by annual earnings and subjective multi-word expressions (MWEs). We applied the conditional random field (CRF) models to identify opinion patterns in the form of MWEs, and our approach outperformed previous work employing unigram models. Moreover, our novel algorithms take the lead to discover the evidences that support the common belief that there are inconsistencies between the implications of the written statements and the reality indicated by the figures in the financial statements. Unexpected negative earnings are often accompanied by ambiguous and mild statements and sometimes by promises of glorious future. © 2011 IEEE.
    關聯: Proceedings - 2011 8th IEEE International Conference on e-Business Engineering, ICEBE 2011, 論文編號 6104589,1-8
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1109/ICEBE.2011.47
    DOI: 10.1109/ICEBE.2011.47
    显示于类别:[資訊科學系] 會議論文

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